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JOURNAL ARTICLE
RESEARCH SUPPORT, N.I.H., EXTRAMURAL
RESEARCH SUPPORT, NON-U.S. GOV'T
RESEARCH SUPPORT, U.S. GOV'T, NON-P.H.S.
Pred-hERG: A Novel web-Accessible Computational Tool for Predicting Cardiac Toxicity.
Molecular Informatics 2015 October
The blockage of the hERG K(+) channels is closely associated with lethal cardiac arrhythmia. The notorious ligand promiscuity of this channel earmarked hERG as one of the most important antitargets to be considered in early stages of drug development process. Herein we report on the development of an innovative and freely accessible web server for early identification of putative hERG blockers and non-blockers in chemical libraries. We have collected the largest publicly available curated hERG dataset of 5,984 compounds. We succeed in developing robust and externally predictive binary (CCR≈0.8) and multiclass models (accuracy≈0.7). These models are available as a web-service freely available for public at https://labmol.farmacia.ufg.br/predherg/. Three following outcomes are available for the users: prediction by binary model, prediction by multi-class model, and the probability maps of atomic contribution. The Pred-hERG will be continuously updated and upgraded as new information became available.
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